The present disclosure relates generally to computer implemented methods and apparatus for processing search queries. More particularly, the disclosure relates to performing dynamic pruning during top-k query processing by search engines.
The search process applied by most modern search engines is usually based on two phases. In the first phase, a large subset of documents that “match” the query is scored by a simple and easy to compute scoring function. The top-k scored documents are extracted by a top-k query processing algorithm. Typically, the extracted list contains a few hundreds, or even thousands, of matching documents. In the second “re-ranking” phase, this extracted list is re-ranked using a complex scoring function that considers a rich set of features of the documents, the query, the context of the search process, and many other signals, in order to obtain a small ranked list of high-quality search results. This disclosure focuses on improving the first phase of the search process, by addressing a novel improvement for dynamic pruning methods for the top-k query processing algorithm.